探勘資料流中常見資料項集技術是近來重要的研究方向，在實際應用中，大部份的使用者對最近的資訊較有興趣，而採用滑動視窗定義資料範圍，可有效探勘出資料流中最近常見資料項集。因此本論文提出一個稱為一般化出現頻率改變點(NFCP)演算法，不需記錄滑動視窗中所有交易內容，以類似FP¬-tree的結構儲存資料項集出現時間的摘要資訊，即可有效的更新資料項集過時資訊並從中探勘出最近常見資料項集。此外，在探勘常見資料項集時，隨著最小支持度門檻值設定變小，探勘結果通常會隨著呈指數成長，為了有效減少探勘出重複資訊，本論文結合探勘代表樣式的方法，能從儲存結構中快速地近似找出資料流最近常見代表樣式，以進一步精簡探勘結果。由實做NFCP演算法之實驗結果顯示，以維護資料項集出現頻率改變點之摘要資訊，可有效近似探勘出目前交易視窗中的最近常見代表樣式，且保證不會有資料樣式的漏失。此外，NFCP所需的維護時間極少，因此若資料流中並非在每個時間點都需進行探勘，但亦隨時有可能要求進行探勘，則NFCP可以很有效率的維護方式，達到隨時可進行探勘最近常見資料項集的效果，可節省更多的處理成本。

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